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S. Evan Staton

dblp:163/5977 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genomics
0.212015
Transposome: a toolkit for annotation of transposable element families from unassembled sequence reads · Bioinform. 2015
Bioinformatics and computational biology › genome annotation
transposable element annotation
0.212015
Transposome: a toolkit for annotation of transposable element families from unassembled sequence reads · Bioinform. 2015

Methods — techniques the papers use, named apart from their topics

whole-genome shotgun sequencing analysis · 0.2
YearPublicationVenuePosition
2015 Transposome: a toolkit for annotation of transposable element families from unassembled sequence reads
abstract
MOTIVATION: Transposable elements (TEs) can be found in virtually all eukaryotic genomes and have the potential to produce evolutionary novelty. Despite the broad taxonomic distribution of TEs, the evolutionary history of these sequences is largely unknown for many taxa due to a lack of genomic resources and identification methods. Given that most TE annotation methods are designed to work on genome assemblies, we sought to develop a method to provide a fine-grained classification of TEs from DNA sequence reads. Here, we present a toolkit for the efficient annotation of TE families from low-coverage whole-genome shotgun (WGS) data, enabling the rapid identification of TEs in a large number of taxa. We compared our software, Transposome, with other approaches for annotating repeats from WGS data, and we show that it offers significant improvements in run time and produces more precise estimates of genomic repeat abundance. Transposome may also be used as a general toolkit for working with Next Generation Sequencing (NGS) data, and for constructing custom genome analysis pipelines. AVAILABILITY AND IMPLEMENTATION: The source code for Transposome is freely available (http://sestaton.github.io/Transposome), implemented in Perl and is supported on Linux.
S. Evan Staton, John M. Burke
Bioinform.1